云南松三种同域共存切梢小蠹梢转干期的空间分布格局

分布在我国西南地区的横坑切梢小蠹,云南切梢小蠹和短毛切梢小蠹同域危害寄主云南松,给林业生产带来巨大损失。为探讨同域切梢小蠹种群在共存下对其空间分布格局的影响,采用传统聚集指标法和地统计学方法研究了三者在梢转干期不同受害云南松纯林树冠中的空间分布型。结果表明重度受害样地中云南切梢小蠹种群密度显著高于横坑切梢小蠹,在轻度受害样地则相反;传统聚集指标法结果显示同域共存的3种切梢小蠹种群在不同受害程度云南松中均为聚集分布,横坑切梢小蠹和云南切梢小蠹聚集是由环境因素和昆虫本身的聚集习性引起;地统计学结果表明除重度受害样地中短毛切梢小蠹呈随机分布外,其余切梢小蠹在不同种群密度下均呈聚集分布;除重度受害样地横坑切梢小蠹外,其他小蠹的空间依赖范围为4.01—7.45 m。横坑切梢小蠹和云南切梢小蠹在不同受害林分中拟合的半变异函数模型在球形模型和高斯模型之间转换。同域共存关系不影响不同种群密度下的切梢小蠹种群空间分布类型,但影响其半变异函数模型和理论参数。

Spatial distribution patterns of three sympatric Tomicus species initially infesting Pinus yunnanensis trunks

Three bark beetles, Tomicus minor, T. yunnanensis and T. brevipilosus, are distributed in southwest China and mainly infest Pinus yunnanensis, causing serious damage to forestry production. In order to study the effect of the relationship of coexistence among three sympatric Tomicus species on their spatial distribution, the spatial distribution patterns of different degrees of infestation in the trunk were analyzed with geostatistical and traditional aggregation index methods. The results showed that the population density of T. yunnanensis was significant higher than that of T. minor in the heavily infested stand, contrary to the lightly infested stand. The results from the traditional index method showed that the spatial distribution patterns of three sympatric Tomicus species were all aggregated in the different degrees of infestation stands. The aggregation distribution of T. minor and T. yunnanensis resulted from their aggregation behavior and environment. The results from the geostatistical method showed that all presented the aggregation distribution, in addition to T. brevipilosus in the heavily infested stand. The level of spatial dependence of all populations ranged from 4.01 to 7.45 m, except the T. minor population in the heavily infested stand. The semivariogram models of T. minor and T. yunnanensis switched between a spherical model and a gaussian model. In short, the coexistence of three sympatric Tomicus species in different population densities did not affect their spatial distribution patterns, but impacted the semivariogram models and model parameters.